Study on the suitablearea of Camellia luteoflora Y. K. Li in China based on MaxEnt model
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College of Life Sciences, Sichuan University

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Q948.5

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    The rare plant Camellia luteoflora Y. K. Li has shrunk in the natural distribution area and is at risk of extinction. In order to analyze the potentially suitable distribution area of C.luteoflora under the current climate and environmental conditions, Maximum Entropy Model (MaxEnt) and Geographic Information System (ArcGIS) were used to predict the suitable distribution areas of C.luteoflora and to explore the dominant environmental factors. The results show that Luzhou, Yibin, Zunyi, Zhaotong, Kunming, Jiangjin and Qijiang of Chongqing are the highly suitable areas for C.luteoflora (fitness index>0.54), and the junction of Guizhou, Sichuan and Chongqing is its core distribution area. The results of the jackknife test showed that the main environmental factors affecting the distribution area of C.luteoflora included the average temperature of the hottest quarter (bio 10), the precipitation of the hottest quarter (bio 18) and the precipitation of the coldest quarter (bio 19), with a cumulative contribution rate of 90.8%. The results of statistical analysis of environmental factors in the suitable area show that the highest temperature in the hottest month is 22.5~27.5 ℃, the average temperature in the hottest season is 11.1~18 ℃, the precipitation in the wettest month is 290~500 mm, the precipitation in the hottest season is 4.4~6.6 mm, the precipitation in the coldest season is 16.7~24.8 mm, the altitude is 450~1 000 m, the slope direction is in the range of -40°~190°, and the slope is between 20°~64°, which is the most suitable niche parameter for C.luteoflora. In addition to the three reported natural distribution areas, the prediction results show that there may still be undiscovered growth areas of C.luteoflora, and field surveys are needed.

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Cite this article as: DAI Yu-Xuan, JIN Tang, XU Hai-Xia, WANG Dong, WANG Li. Study on the suitablearea of Camellia luteoflora Y. K. Li in China based on MaxEnt model [J]. J Sichuan Univ: Nat Sci Ed, 2021, 58: 026002.

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History
  • Received:July 18,2020
  • Revised:September 28,2020
  • Adopted:November 03,2020
  • Online: April 02,2021
  • Published: